RAG Security

RAG: Retrieval-Augmented Generation

Overview

RAG security examines how threats can enter through the knowledge corpus, retriever, retrieved context, and generator, including poisoned documents, prompt injection, private-data extraction, and unsafe answers. Attacks and defenses are tested in question-answering, multi-hop, web-search, and agentic settings, using benchmarks that measure answer quality, leakage, attack success, and abstention. Defenses include document screening and provenance checks, robust reranking and evidence aggregation, cross-source verification, query-time privacy controls, and encrypted or differentially private retrieval. A central challenge is resisting adaptive attacks across the full pipeline without sacrificing retrieval utility, increasing latency, or relying on assumptions such as a trusted majority of documents.

Latest papers

CardsList

106 papers10 papers in the last four weeks, level with the four weeks before. 0.1% of all new papers.

  1. Supercharging Federated Intelligence Retrieval

    Mar 26, 2026Dimitris Stripelis, Patrick Foley, Mohammad Naseri +4Privacy-Preserving RAGRetrieval-Augmented Generation

  2. ProGRank: Probe-Gradient Reranking to Defend Dense-Retriever RAG from Corpus Poisoning

    Mar 24, 2026Xiangyu Yin, Yi Qi, Chih-Hong ChengRAG SecurityRAG Poisoning Attacks

  3. Towards Secure Retrieval-Augmented Generation: A Comprehensive Review of Threats, Defenses and Benchmarks

    Mar 23, 2026Yanming Mu, Hao Hu, Feiyang Li +7RAG SecurityRAG Robustness

  4. Towards Unsupervised Adversarial Document Detection in Retrieval Augmented Generation Systems

    Mar 17, 2026Patrick LeviRAG SecurityRAG Poisoning Attacks

  5. P2^2RAG: Efficient Privacy-Preserving RAG Service Supporting Arbitrary Top-kk Retrieval

    Mar 16, 2026Yulong Ming, Mingyue Wang, Jijia Yang +4Privacy-Preserving RAGRAG Security

  6. Sensitivity-Aware Retrieval-Augmented Intent Clarification

    Mar 6, 2026Maik LarooijConversational SearchRAG Security

  7. Adversarial Hubness Detector: Detecting Hubness Poisoning in Retrieval-Augmented Generation Systems

    Feb 25, 2026Idan Habler, Vineeth Sai Narajala, Stav Koren +2RAG SecurityRAG Poisoning Attacks

  8. Adversarial Intent is a Latent Variable: Stateful Trust Inference for Securing Multimodal Agentic RAG

    Feb 24, 2026Inderjeet Singh, Vikas Pahuja, Aishvariya Priya Rathina Sabapathy +8AI Agent SecurityRAG Security

  9. Retrieval Collapses When AI Pollutes the Web

    Feb 18, 2026Hongyeon Yu, Dongchan Kim, Young-Bum KimInformation RetrievalRAG Robustness

  10. Eyes-on-Me: Scalable RAG Poisoning through Transferable Attention-Steering Attractors

    Oct 1, 2025Yen-Shan Chen, Sian-Yao Huang, Cheng-Lin Yang +1Language Model SteeringRAG Poisoning Attacks

  11. Knowing When Not to Answer: Lightweight KB-Aligned OOD Detection for Safe RAG

    Aug 4, 2025Ilias Triantafyllopoulos, Renyi Qu, Salvatore Giorgi +3RAG SecurityOOD Detection

  12. Learning to Erase Private Knowledge from Multi-Documents for Retrieval-Augmented Large Language Models

    Apr 14, 2025Yujing Wang, Jinwen Chen, Hainan Zhang +5Retrieval-Augmented GenerationPrivacy Leakage in Language Models

  13. BadRAG: Identifying Vulnerabilities in Retrieval Augmented Generation of Large Language Models

    Jun 3, 2024Jiaqi Xue, Mengxin Zheng, Yebowen Hu +3LLM Backdoor AttacksRAG Poisoning Attacks